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These typically leverage the techniques learned from statistical machine learning, coupled with ensemble architectures that create multiple feature detection models.
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For multiple figures, feature detection occurs in the first layer while figure-ground segregation is observed in the second layer and border-ownership in the final layer.
Typical post-processing pipelines for large MS data-sets proceed through multiple stages, with feature detection and alignment being the two most critical ones (Katajamaa and Oresic 2007).
In this project, we have further developed a computer-aided detection tool, the adaptive multiple feature method (AMFM), for the detection of interstitial lung diseases based on MDCT-generated volumetric data.
A number of spectrum sensing methods have been proposed for CR systems, such as energy detection (ED), cyclostationarity feature detection, second-order statistics detection, matched-filtering detection, compressive sensing detection [7, 8], and multiple antenna detection [9].
Inspired by the multiple scale feature extraction and weighted dissimilarity calculation methods of models for "visual saliency" [35, 36], we designed our local feature detection method for visual secret sharing schemes specifically.
Image feature detection, aspect ratio, scale, crop.
And with luck, feature detection at higher and lower levels.
Q: No one is talking about CSS feature detection.
This paper deals with signal feature detection.
Feature detection is presented in Section 'Feature extraction'.
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